Integrated Sales Lead Matching With Adaptive Scheduling
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Solution Overview
Problem
Existing sales leads matching systems are inefficient, costly, and prone to subjective manual processes, failing to consider rapidly changing variables and optimal resource matching.
Innovation Solution
A computer-based sales leads matching system utilizing algorithms that integrate lead data, sales resources, and historical data to create dynamic schedules, self-learn, and refine matching algorithms for optimal resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processes are used to select and match sales leads with sales resources, then personnel can exercise subjective judgment and flexibility, but the process becomes time-consuming and vulnerable to subjective bias
Solution Approach 1:
The system enables self-service through automated algorithms that independently perform lead matching without requiring manual intervention. The algorithm automatically processes lead data, applies matching criteria, and generates assignments, freeing personnel from time-consuming manual matching while maintaining consistent application of matching rules
Solution Approach 2:
The patent replaces the mechanical manual process of lead matching with an automated computational system. The algorithm substitutes human personnel actions with computer-based processing, using data structures and computational logic to perform matching decisions that were previously made manually, thereby reducing time consumption while preserving matching quality
2Measurement precision
If comprehensive algorithms are used to match sales leads with sales resources, then matching precision and efficiency are improved, but system complexity and development costs increase
Solution Approach 1:
The matching system is segmented into distinct functional modules: data input module for receiving lead and resource data, algorithm processing module for performing matching calculations, and output module for generating assignments. This segmentation allows the complex matching logic to be broken down into manageable components, improving maintainability while preserving matching precision
Solution Approach 2:
The algorithm is designed as a universal matching system that can handle multiple types of sales leads and sales resources through a single unified framework. The system uses general-purpose data structures and configurable matching criteria that can be applied across different scenarios without requiring separate specialized systems, thereby reducing overall complexity while maintaining high matching accuracy
3Ease of manufacture
If manual matching processes are used, then implementation costs are reduced initially, but ongoing expenses increase due to variability and inefficiency
Solution Approach 1:
The automated system performs matching operations autonomously without requiring ongoing manual labor for each matching task. Once implemented, the algorithm continuously processes leads and generates assignments independently, eliminating the need for repeated manual intervention and reducing ongoing operational expenses while significantly improving matching efficiency
Solution Approach 2:
The system performs preliminary processing of lead data and resource data during the implementation phase, establishing data structures and matching rules in advance. This preliminary action enables the system to quickly process subsequent matching requests without requiring extensive manual setup for each new batch of leads, thereby improving ongoing productivity while keeping implementation costs manageable
Data Source
AI summary
A computer-based method for managing sales leads matching systems is provided. The method includes the steps of entering potential lead data. The method also includes the steps of inputting available sales resources. The method further includes the steps of loading selected past saved sales schedules. The method additionally includes the steps of updating industry specific data. The method includes the steps of integrating updated sales leads matching algorithm output. The method also includes the steps of creating new sales schedules based on the integrated updated sales leads matching algorithm output. The method further includes the steps of issuing new sales schedules to the available sales resources, recording data from execution of the sales schedules for the available sales resources, calculating a new sales leads matching algorithm output, and utilizing the new sales leads matching algorithm output to develop a next generation of new sales schedules.